code: def __init__(
      self,
      input_channels,
      layers,
      late_downsample=False,
      pretrained=None,
  ):
      super().__init__(
          input_channels,
          layers,
          late_downsample=late_downsample,
          pretrained=pretrained,
      )
      self.input_channels = input_channels
      self.shortcut_inplane = [
          input_channels,
          self.midplanes,
          64,
          128,
          256,
      ]
      self.shortcut_plane = [32, self.midplanes, 64, 128, 256]
  
      self.shortcut = nn.LayerList()
      for stage, inplane in enumerate(self.shortcut_inplane):
          self.shortcut.append(
              self._make_shortcut(inplane, self.shortcut_plane[stage])
          )
  
      self.guidance_head = nn.Sequential(
          nn.Pad2D(1, mode="reflect"),
          nn.utils.spectral_norm(
              nn.Conv2D(
                  3,
                  16,
                  kernel_size=3,
                  padding=0,
                  stride=2,
                  bias_attr=False,
              )
          ),
          nn.ReLU(),
          self._norm_layer(16),
          nn.Pad2D(1, mode="reflect"),
          nn.utils.spectral_norm(
              nn.Conv2D(
                  16,
                  32,
                  kernel_size=3,
                  padding=0,
                  stride=2,
                  bias_attr=False,
              )
          ),
          nn.ReLU(),
          self._norm_layer(32),
          nn.Pad2D(1, mode="reflect"),
          nn.utils.spectral_norm(
              nn.Conv2D(
                  32,
                  128,
                  kernel_size=3,
                  padding=0,
                  stride=2,
                  bias_attr=False,
              )
          ),
          nn.ReLU(),
          self._norm_layer(128),
      )
  
      self.gca = GuidedCxtAtten(128, 128)
  
      self.init_weight()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.utils import utils
  from ppmatting.models.layers import GuidedCxtAtten
label_desc: Use image node_id 1 to create a new ResGuidedCxtAtten object from inherited base classes: ResNet_D with example: obj = ResGuidedCxtAtten(input_channels, layers, late_downsample, pretrained)